{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CSVの読み書き"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 初期設定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# http://qiita.com/hik0107/items/de5785f680096df93efa\n",
    "# グラフ化に必要なものの準備\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Jupyter上に図を表示するためのおまじない\n",
    "%matplotlib inline\n",
    "\n",
    "# データの扱いに必要なライブラリ\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "\n",
    "# チャートがきれいになるおまじない\n",
    "plt.style.use('ggplot') \n",
    "\n",
    "# 日本語化\n",
    "#font = {'family' : 'ipag'}\n",
    "#matplotlib.rc('font', **font)\n",
    "#from matplotlib.font_manager import FontProperties\n",
    "#fp = FontProperties(fname=r'~/.fonts/ipag.ttf', size=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Open関数で読み込み"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name,English,Mathematics,Science\n",
      "Taro,75,90,85\n",
      "Hanako,100,85,80\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "### csvファイルのPATHを設定\n",
    "csv_path='csv/Achievement.csv'\n",
    "\n",
    "### ファイルの作成\n",
    "strs = \"\"\"Name,English,Mathematics,Science\n",
    "Taro,75,90,85\n",
    "Hanako,100,85,80\n",
    "\"\"\"\n",
    "\n",
    "f = open(csv_path, 'w')\n",
    "f.writelines(strs)\n",
    "f.close\n",
    "\n",
    "### ファイルの中身確認\n",
    "f = open(csv_path, \"r\")\n",
    "for line in f:\n",
    "    print(line, end=\"\")\n",
    "print(\"\\n\")\n",
    "\n",
    "### pandasで読み込んで出力\n",
    "df = pd.read_csv(csv_path)\n",
    "df\n",
    "\n",
    "### csv出力\n",
    "df.to_csv( 'csv/output.csv' )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Open関数で書き込み"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Date,Tokushima,Naruto,Anan\n",
      "2020-01-01,5,6,3\n",
      "2020-01-02,6,8,4\n",
      "2020-01-03,9,10,6\n",
      "2020-01-04,4,5,2\n",
      "2020-01-05,5,6,3\n"
     ]
    }
   ],
   "source": [
    "### csvファイルのPATHを設定\n",
    "csv_path='csv/Temperature.csv'\n",
    "\n",
    "### ファイルの作成\n",
    "strs = \"\"\"Date,Tokushima,Naruto,Anan\n",
    "2020-01-01,5,6,3\n",
    "2020-01-02,6,8,4\n",
    "2020-01-03,9,10,6\n",
    "2020-01-04,4,5,2\n",
    "2020-01-05,5,6,3\n",
    "\"\"\"\n",
    "\n",
    "f = open(csv_path, 'w')\n",
    "f.writelines(strs)\n",
    "f.close\n",
    "\n",
    "### ファイルの中身確認\n",
    "f = open(csv_path, \"r\")\n",
    "for line in f:\n",
    "    print(line, end=\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CSVモジュールを利用した読み込み\n",
    "\n",
    "* モジュールを利用した方がロジックなど考えなくてすむので楽"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Name', 'English', 'Mathematics', 'Science']\n",
      "['Taro', '75', '90', '85']\n",
      "['Hanako', '100', '85', '80']\n"
     ]
    }
   ],
   "source": [
    "import csv \n",
    "with open('csv/Achievement.csv', mode='r', encoding='utf-8') as fp:\n",
    "    csv_reader = csv.reader(fp)\n",
    "    for row in csv_reader:\n",
    "        print(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CSVモジュールを利用した書き込み\n",
    "\n",
    "* lineterminator='\\n'\n",
    "    * Windowsだと余計な空行が入るため\n",
    "        * もしくはOpen関数時点の引数で「newline=\"\"」を追加する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "header = ['A', 'B', 'C']\n",
    "data = [[1,2,3], [4,5,6], [7,8,9]]\n",
    "with open('csv/test_w.csv', mode='w', encoding='utf-8') as fp:\n",
    "    csv_writer = csv.writer(fp, lineterminator=\"\\n\")\n",
    "    csv_writer.writerow(header)\n",
    "    csv_writer.writerows(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A,B,C\n",
      "1,2,3\n",
      "4,5,6\n",
      "7,8,9\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "cat csv/test_w.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CSVを読み取ったまま出力"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-01          5       6     3\n",
       "1  2020-01-02          6       8     4\n",
       "2  2020-01-03          9      10     6\n",
       "3  2020-01-04          4       5     2\n",
       "4  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## index_colを変えて出力\n",
    "\n",
    "* indexとする列を指定する\n",
    "    * 数値で指定すると、指定した列がindexになる\n",
    "    * []で複数指定できる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Tokushima  Naruto  Anan\n",
       "Date                               \n",
       "2020-01-01          5       6     3\n",
       "2020-01-02          6       8     4\n",
       "2020-01-03          9      10     6\n",
       "2020-01-04          4       5     2\n",
       "2020-01-05          5       6     3"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tokushima</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Date  Naruto  Anan\n",
       "Tokushima                          \n",
       "5          2020-01-01       6     3\n",
       "6          2020-01-02       8     4\n",
       "9          2020-01-03      10     6\n",
       "4          2020-01-04       5     2\n",
       "5          2020-01-05       6     3"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Naruto</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date  Tokushima  Anan\n",
       "Naruto                             \n",
       "6       2020-01-01          5     3\n",
       "8       2020-01-02          6     4\n",
       "10      2020-01-03          9     6\n",
       "5       2020-01-04          4     2\n",
       "6       2020-01-05          5     3"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=2)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th>Naruto</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <th>8</th>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <th>10</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Tokushima  Anan\n",
       "Date       Naruto                 \n",
       "2020-01-01 6               5     3\n",
       "2020-01-02 8               6     4\n",
       "2020-01-03 10              9     6\n",
       "2020-01-04 5               4     2\n",
       "2020-01-05 6               5     3"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=[0,2])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## headerを変えて出力\n",
    "\n",
    "* 指定した行がheaderになる\n",
    "* 複数行をheaderとして扱う場合は[]を使う\n",
    "    * 一つだけなのに[]を使うと値がNaNになる\n",
    "    * 行を飛び飛びで指定すると、headerに指定されなかった行は除去される"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-01          5       6     3\n",
       "1  2020-01-02          6       8     4\n",
       "2  2020-01-03          9      10     6\n",
       "3  2020-01-04          4       5     2\n",
       "4  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Date Tokushima Naruto Anan\n",
       "0  NaN       NaN    NaN  NaN\n",
       "1  NaN       NaN    NaN  NaN\n",
       "2  NaN       NaN    NaN  NaN\n",
       "3  NaN       NaN    NaN  NaN\n",
       "4  NaN       NaN    NaN  NaN"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=[0])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2020-01-01  5   6  3\n",
       "0  2020-01-02  6   8  4\n",
       "1  2020-01-03  9  10  6\n",
       "2  2020-01-04  4   5  2\n",
       "3  2020-01-05  5   6  3"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  2020-01-01    5    6    3\n",
       "0        NaN  NaN  NaN  NaN\n",
       "1        NaN  NaN  NaN  NaN\n",
       "2        NaN  NaN  NaN  NaN\n",
       "3        NaN  NaN  NaN  NaN"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=[1])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date Tokushima Naruto Anan\n",
       "   2020-01-01         5      6    3\n",
       "0  2020-01-02         6      8    4\n",
       "1  2020-01-03         9     10    6\n",
       "2  2020-01-04         4      5    2\n",
       "3  2020-01-05         5      6    3"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=[0, 1])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>2020-01-02</th>\n",
       "      <th>6</th>\n",
       "      <th>8</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date Tokushima Naruto Anan\n",
       "   2020-01-01         5      6    3\n",
       "   2020-01-02         6      8    4\n",
       "0  2020-01-03         9     10    6\n",
       "1  2020-01-04         4      5    2\n",
       "2  2020-01-05         5      6    3"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=[0, 1, 2])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>2020-01-02</th>\n",
       "      <th>6</th>\n",
       "      <th>8</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>2020-01-04</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date Tokushima Naruto Anan\n",
       "   2020-01-02         6      8    4\n",
       "   2020-01-04         4      5    2\n",
       "0  2020-01-05         5      6    3"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, header=[0, 2, 4])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## skiprowsを変えて出力\n",
    "\n",
    "* 指定した行をスキップする\n",
    "    * 数値で指定すると、上から指定した行数飛ばして読み込む\n",
    "    * []で複数指定すると、指定した行だけスキップする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-01          5       6     3\n",
       "1  2020-01-02          6       8     4\n",
       "2  2020-01-03          9      10     6\n",
       "3  2020-01-04          4       5     2\n",
       "4  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2020-01-01  5   6  3\n",
       "0  2020-01-02  6   8  4\n",
       "1  2020-01-03  9  10  6\n",
       "2  2020-01-04  4   5  2\n",
       "3  2020-01-05  5   6  3"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-01-02</th>\n",
       "      <th>6</th>\n",
       "      <th>8</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2020-01-02  6   8  4\n",
       "0  2020-01-03  9  10  6\n",
       "1  2020-01-04  4   5  2\n",
       "2  2020-01-05  5   6  3"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=2)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-01-01</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2020-01-01  5   6  3\n",
       "0  2020-01-02  6   8  4\n",
       "1  2020-01-03  9  10  6\n",
       "2  2020-01-04  4   5  2\n",
       "3  2020-01-05  5   6  3"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=[0])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-02          6       8     4\n",
       "1  2020-01-03          9      10     6\n",
       "2  2020-01-04          4       5     2\n",
       "3  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=[1])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-01          5       6     3\n",
       "1  2020-01-03          9      10     6\n",
       "2  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, skiprows=[2,4])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 棒グラフで描画するようのデータに成形する\n",
    "\n",
    "* index_colは日付を利用\n",
    "* Tokushima, Narutoのみ使う\n",
    "* 徳島,鳴門と漢字にする\n",
    "* index(Date)列はdatetime型に変換する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Tokushima  Naruto  Anan\n",
       "0  2020-01-01          5       6     3\n",
       "1  2020-01-02          6       8     4\n",
       "2  2020-01-03          9      10     6\n",
       "3  2020-01-04          4       5     2\n",
       "4  2020-01-05          5       6     3"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "      <th>Anan</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Tokushima  Naruto  Anan\n",
       "Date                               \n",
       "2020-01-01          5       6     3\n",
       "2020-01-02          6       8     4\n",
       "2020-01-03          9      10     6\n",
       "2020-01-04          4       5     2\n",
       "2020-01-05          5       6     3"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tokushima</th>\n",
       "      <th>Naruto</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Tokushima  Naruto\n",
       "Date                         \n",
       "2020-01-01          5       6\n",
       "2020-01-02          6       8\n",
       "2020-01-03          9      10\n",
       "2020-01-04          4       5\n",
       "2020-01-05          5       6"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=0)\n",
    "\n",
    "# 1列目(index_col=0で指定された列Date)はindexなのでiloc[0]はDateではなくTokushimaになる\n",
    "df = df.iloc[:, [0, 1]]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>徳島</th>\n",
       "      <th>鳴門</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            徳島  鳴門\n",
       "Date              \n",
       "2020-01-01   5   6\n",
       "2020-01-02   6   8\n",
       "2020-01-03   9  10\n",
       "2020-01-04   4   5\n",
       "2020-01-05   5   6"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=0)\n",
    "\n",
    "df = df.iloc[:, [0, 1]]\n",
    "df.columns = [u'徳島', u'鳴門']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>徳島</th>\n",
       "      <th>鳴門</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            徳島  鳴門\n",
       "Date              \n",
       "2020-01-01   5   6\n",
       "2020-01-02   6   8\n",
       "2020-01-03   9  10\n",
       "2020-01-04   4   5\n",
       "2020-01-05   5   6"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path, index_col=0)\n",
    "\n",
    "df = df.iloc[:, [0, 1]]\n",
    "df.columns = [u'徳島', u'鳴門']\n",
    "df.index = pd.to_datetime(df.index)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f7cd0523f60>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uo7LaJp5emUfqoVKmdg1h3rh4Ql18W/65tGFgvP9/kJeF6faHUfEdHR1Sq6Ti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\nhOrUzdEhOZw2DDi05/szhzeDuQk6dkX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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7ca636d3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
